Optimization Engineering

Fix Bottlenecks.
Scale Effortlessly.

Stop guessing why your app is slow. Use AI to analyze flame graphs, traces, and code hot paths with senior judgment.

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Why standard profiling is a headache

Reading production traces and GC logs is a specialized skill that takes years to master. AI changes the game by acting as an expert interpreter.

Traditional Profiling
  • Staring at binary dumps for hours
  • Guess-and-check optimization cycles
  • Missing subtle N+1 queries in complex loops
AI-Accelerated Profiling
  • Convert logs to plain-text insights instantly
  • AI-suggested architectural fixes for hot paths
  • Automated memory leak pattern detection

Optimizing for the Real World

Learn how to leverage AI across the entire performance stack.

01

Profiling 101 with AI

Feed AI your flame graphs and learn how to ask for the 'heavy lifters' in your code base.

02

Latency Analysis

Systematically reduce TTFB (Time to First Byte) by analyzing request/response cycles.

03

Memory Leak Hunting

Identify heap growth patterns and find where objects are sticking around longer than they should.

04

Hot-Path Optimization

Learn when to refactor for performance and when to let AI rewrite critical loops in lower-level logic.

05

Load Test Synthesis

Use AI to generate complex load test scenarios that reveal architectural weaknesses before launch.

06

Continuous Monitoring

Setup AI alerts that understand 'baseline shift' vs 'normal spikes' in production metrics.

FAQ

Yes, when given the right context. We teach you how to feed profiling data, flame graphs, and network traces to AI tools to identify exactly where cycles are being wasted.

No. The principles of performance optimization—profiling, data analysis, and algorithmic improvements—are language-agnostic. Whether you're in Node, Go, PHP, or Python, the workflow stays the same.

No. This course teaches you how to use AI as your expert performance consultant, helping you interpret complex metrics and suggest high-impact fixes.